An explainable feature selection framework for web phishing detection with machine learning by Sakib Shahriar Shafin

“…In the evolving landscape of cyber threats, phishing attacks pose significant challenges, particularly through deceptive webpages designed to extract sensitive information under the guise of legitimacy. Conventional and machine learning (ML)-based detection systems struggle to detect phishing websites owing to their constantly changing tactics. …”
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Unlocking biological complexity: the role of machine learning in integrative multi-omics by Ravindra Kumar, Rajrani Ruhel, Andre J. van Wijnen

“…It offers sophisticated algorithms that can identify and discover hidden patterns and provide insights into complex biological networks. …”
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Application of machine learning algorithm to predict the behavior of stocks marketed in Brazil by Gabriel Donadio Costa, Rogério João Lunkes

“…In order to assist investors in the decision-making process, artificial intelligence tools aim at finding patterns hidden in data and providing useful, timely and accurate information. …”
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Specifics of predicting the profitability of individual bank products based on machine learning by Inna Strelchenko, Dmytro Stognii, Anatolii Strelchenko

“…It explores the use of machine learning to build adaptive predictive models that can identify hidden patterns in financial data and provide more accurate estimates of the future profitability of banking products. …”
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Advancing agriculture with machine learning: a new frontier in weed management by Mohammad MEHDIZADEH, Duraid K. A. AL-TAEY, Anahita OMIDI, Aljanabi Hadi Yasir ABBOOD, Shavan ASKAR, Soxibjon TOPILDIYEV, Harikumar PALLATHADKA, Renas Rajab ASAAD

“…This review examines the potential of machine learning in chemical weed management. Machine learning offers innovative and sustainable approaches by analyzing large data sets, recognizing patterns, and making accurate predictions. …”
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A Novel Hybrid Machine Learning Framework for Wind Speed Prediction by Rhafes Mohamed Yassine, Moussaoui Omar, Raboaca Maria Simona, Mihaltan Traian Candin

“…However, using wind power is challenging due to the variability and unpredictability of wind patterns. Consequently, the ability to predict wind power in advance is crucial. …”
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Devising a Breast Cancer Diagnosis Protocol through Machine Learning by Tooba Mujtaba, Saif Ullah Hashmi, Usama Bin Imtiaz, Sheikh Jameel Fathima Nusra

“…The support vector machine (SVM) and decision tree models of machine learning were used to evaluate the prognostic and diagnostic significance. …”
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Evaluating Global Machine Learning Models for Tropical Cyclone Dynamics and Thermodynamics by Pankaj Lal Sahu, Sukumaran Sandeep, Hariprasad Kodamana

“…MLWP models realistically captured the absolute vorticity patterns and their advection, demonstrating their ability to represent the dynamics underlying TC translation. …”
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Machine Learning Advancements in Urban Traffic Simulation: A Comprehensive Survey by Harshit Maheshwari, Li Yang, Richard W. Pazzi

“…Traditional simulation models often struggle to capture the intricacies of urban traffic patterns, leading to unrealistic simulations, which negatively affect traffic management and urban planning. …”
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Research on Machine Vision–Based Intelligent Tracking System for Maintenance Personnel by Yinglin Ma, Hongmei Shi, Yao Wang, Baofeng Li

“…Traditional manual monitoring demands substantial manpower and is prone to human error, whereas machine vision–based intelligent monitoring offers a promising alternative, reducing the dispatch control center (DCC) workload while enhancing safety management. …”
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Alloys innovation through machine learning: a statistical literature review by Alireza Valizadeh, Ryoji Sahara, Maaouia Souissi

“…The review presents a comprehensive overview of different aspects of alloy innovation by machine learning and other computational approaches used in recent years. …”
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On the use of adversarial validation for quantifying dissimilarity in geospatial machine learning prediction by Yanwen Wang, Mahdi Khodadadzadeh, Raúl Zurita-Milla

“…Recent geospatial machine learning studies have shown that the results of model evaluation via cross-validation (CV) are strongly affected by the dissimilarity between the sample data and the prediction locations. …”
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Healthcare Prediction Using Novel Machine Learning Methods and Metaheuristic Algorithm by Yazdan Ashgevari, Behrouz Alefy, Faranak Kazemi

“…These days, machine learning (ML) is one of the most important technologies, especially in the field of healthcare. …”
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Machine Learning Applications in Use-Wear Analysis: A Critical Review by Anastasia Eleftheriadou, Shannon P. McPherron, João Marreiros

“…Use-wear analysis examines the macroscopic and microscopic patterns of traces left on tool surfaces as a result of use. …”
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Machine learning classification of consumption habits of creatine supplements in gym goers by Patrícia C. Magalhães, Samuel Encarnação, Andre C. Schneider, Pedro Forte, José Teixeira, Antonio Miguel Monteiro, Tiago M. Barbosa, Ana M. Pereira

“…The aim is to identify usage patterns and the main factors that influence creatine supplementation, providing a basis for future educational interventions and recommendations for safe and effective use. …”
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TBM shield mud cake prediction model based on machine learning by Qi Zhang, Peng Xu, Jing Zhang, Zhao Yang, Yu Li, Xintong Kong, Xiao Yuan

“…IntroductionDuring tunnel boring machine (TBM) shield tunneling in clayey strata, the excavated soil consolidates on the cutter head or cutting tools, forming mud cakes that significantly impact the efficiency of shield tunneling.MethodsTo predict mud cakes during shield tunneling, four distinct supervised machine learning models, including logistic regression, support vector machine, random forest, and BP neural network were employed. …”
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Interpretable Machine Learning reveals the Role of PANoptosis in the Diagnosis and Subtyping of NAFLD by Feng Tian, Yuqi Zhao, Xinyang He, Yu Zhang, Minxuan Hu, Yiwei Liang, Ziyou Tian, Yaxian Gao, Yongwei Wang

“…Here, we integrated multiple datasets and interpretable machine learning to unravel the role of PANoptosis in NAFLD diagnosis, subtyping, and immune microenvironment remodeling. …”
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Predictive athlete performance modeling with machine learning and biometric data integration by Qin Jianjun, Haytham F. Isleem, Walaa J. K. Almoghayer, Mohammad Khishe

“…Abstract The Purpose of this study is to propose a new integrative framework for athletic performance prediction based on state-of-the-art machine learning analysis and biometric data biometric scanning. …”
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Moisture prediction in chicken litter using hyperspectral data and machine learning by Ahmad Tulsi, Abdul Momin, Victoria Ayres

“…These results reveal a key insight: preprocessing enhances linear model accuracy but may suppress critical non-linear patterns needed by tree-based models like XGBoost. …”
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Leveraging machine learning for data-driven building energy rate prediction by Nasim Eslamirad, Mehdi Golamnia, Payam Sajadi, Francesco Pilla

“…These findings underscore the effectiveness of ML in Urban Building Energy Modelling (UBEM), particularly in forecasting energy consumption patterns and identifying high-energy-use buildings. …”
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